1 / 25

Ant Colony Optimization Chapter 5

Ant Colony Optimization Chapter 5. Ant Colony Optimization for NP-Hard Problems Ben Sauskojus. NP-Hard Problem Types. Routing Problems Assignment Problems Scheduling Problems. Routing Problems. Agents visiting locations Objective depends on order locations are visited. Routing Problems.

travisbaker
Download Presentation

Ant Colony Optimization Chapter 5

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Ant Colony Optimization Chapter 5 Ant Colony Optimization for NP-Hard Problems Ben Sauskojus

  2. NP-Hard Problem Types • Routing Problems • Assignment Problems • Scheduling Problems

  3. Routing Problems • Agents visiting locations • Objective depends on order locations are visited

  4. Routing Problems • Sequential Ordering Problem (SOP) • Generalized asymmetric TSP • Has precedence constraints • Application: ACS based. Top performers use local search (3-opt)

  5. Routing Problems • Vehicle Routing Problem (VRP) • http://www.dna-evolutions.com/dnaappletsample.html • Capacitated (CVRP) • Each customer needs a specific amount of goods

  6. Vehicle Routing Problem • Objectives • Each customer is served by one vehicle • Vehicles start and end at Depot • Vehicles cannot deliver more than overall capacity • Subproblems • TSP • Bin packing problem

  7. Vehicle Routing Problem • Application: AS-rank based.

  8. Vehicle Routing Problem • Time Window (VRPTW) • Each customer has a time window in which they must be served • Objectives • Minimize the number of vehicles (routes) • Minimize travel time • Application • Multiple ACS (Two layered colonies)

  9. Assignment Problems • Assign a set of items to resources • Two assignment Types • Assignment order • Assignment to specific resources

  10. Quadratic Assignment (QAP) • Assigning facilities to locations • Objectives • Minimize the sum of the products between flows and distances

  11. Quadratic Assignment (QAP) • Example • Facilities are ‘Bathrooms’ • ‘Main work Area’ • ‘Parking Lot’

  12. General Assignment (GAP) • Tasks are assigned to Agents • Each Agent has limited capacity • Each Task consumes some of an Agent’s capacity • Assigning tasks incurs a cost • Objectives • Find a feasible task assignment of minimum cost

  13. General Assignment (GAP) • Application: MMAS-based • Only one ant • Only feasible solutions get pheromone • Pheromone has nothing to do with solution quality

  14. General Assignment (GAP)

  15. Scheduling Problems • Allocating scarce resources to tasks over time • Definition: An operation is a job that has to be processed on more than one machine. Example: building a car • Note: Processing time are fixed and job cannot be interrupted

  16. Single-Machine Total Weighted Tardiness (SMTWTP) • Jobs have to be processed sequentially on a single machine • Each job has: • Processing time • Weight • Due date

  17. Single-Machine Total Weighted Tardiness (SMTWTP)

  18. Single-Machine Total Weighted Tardiness (SMTWTP) • Pheromone trails refer to the desirability of scheduling a job to the i-th position • Application: ACS based and is one of the best algorithms for the problem

  19. Job Shop, Open Shop, Group Shop • Given: • A set of Operations • A set of Machines that can only do specific operations • A set of Jobs which consist of operations • Each operation has a processing time

  20. Job Shop, Open Shop, Group Shop • Job Shop (JSP) • Precedence constraints which induce a total ordering • Example: Robbing a bank • Open Shop (OSP) • No precedence constraints • Example: Employee scheduling,Cleaning house

  21. Job Shop, Open Shop, Group Shop • Group Shop (GSP) • Operations are arranged in group. • Groups must be completed in some order • Operations inside groups can be done in any order • Example: Commercial Cleaning

  22. Job Shop, Open Shop, Group Shop • Objectives • Minimize the completion time of the last task (Makespan) • Applications • AS based used for JSP (performs poorly) • AntQ based for OSP (performs poorly) • MMAS based for GSP (performs well)

  23. Job Shop, Open Shop, Group Shop • Pheromones • JSP and OSP pheromones refer to the desirability of scheduling operation j directly after i • GSP pheromones refer to the desirability of scheduling operation j sometime after i

  24. Resource-Constrained Project Scheduling (RCPSP) • Given • Activities with precedence constraints, processing times, and resource requirements • Non-reusable resources • Objectives • Assign to each activity a start time minimizing makespan

  25. Resource-Constrained Project Scheduling (RCPSP)

More Related